MIMO Radar Antenna Array Calibration for DoA Estimation with Super-resolution Algorithms
Multiple-input-multiple-output (MIMO) radar has been widely applied for high angular resolution in many fields. The MIMO radar utilizes transmitter and receiver antenna arrays with multiple elements to form a virtual array to realize direction of arrival (DoA) estimation. The DoA estimation can be realized by digital beamforming (DBF) and the performance could be further improved through advanced algorithm.
Super-resolution algorithms like Capon, MUSIC or ESPRIT are popular for improving the angular resolution for DoA estimation. All the DoA estimation algorithms are degraded due to antenna array errors (amplitude and/or phase error, mutual coupling and position error). The impact of antenna array error for classical beamforming has been widely discussed in the literature. However, the impact for super-resolution algorithm has not been sufficiently analyzed.
In this MS project, the student needs in a first phase to study the performance of super-resolution algorithms under various antenna arrays errors. In a second phase, he will propose calibration strategies and algorithms.
The student will study and compare state-of-the-art algorithms and, if possible, propose improved or novel approaches for MIMO antenna calibration. The calibration algorithm is expected to be implemented online and, ideally, without known reference targets. Two environments will be considered: indoor environments, where the challenge is multipath propagation, and outdoor environments, where the challenge is the motion of the radar platform.
The work will include:
· State-of-the-art study
· Implementation of super-resolution DoA estimation for MIMO radar
· Simulation of MIMO antenna error and performance analysis
· Implementation and analysis of phase calibration using state-of-the-art algorithm
· Investigation of innovative approaches of array calibration (for indoor and outdoor environment)
· Test using real MIMO radar recordings
The successful candidate must show a strong understanding of signal processing and linear algebra. Proficiency with Matlab or python is a must. Some knowledge of radar concepts is a plus
- Master Thesis internship (6 months)
- Preceded by optional summer internship (3 months)
Responsible scientist(s): Ruoyu Feng (Ruoyu.Feng@imec.be), PhD Researcher
Type of project: Combination of internship and thesis
Duration: 6 months
Required degree: Master of Engineering Science, Master of Engineering Technology
Required background: Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Ruoyu Feng (Ruoyu.Feng@imec.be)
Only for self-supporting students.